Multi sensor system for classifying Harumanis mango based on external and internal quality
This thesis presents a multi sensor system for classifying Harumanis mango based on its external and internal quality. Both external and internal quality of Harumanis mango affects the consumer buying preferences. Current method of classifying Harumanis mango is done manually and destructive for its...
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| Format: | Thesis |
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| Language: | English |
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78037/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78037/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/78037/3/Mohd%20Firdaus.pdf |
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| Summary: | This thesis presents a multi sensor system for classifying Harumanis mango based on its external and internal quality. Both external and internal quality of Harumanis mango affects the consumer buying preferences. Current method of classifying Harumanis mango is done manually and destructive for its internal quality determination. The proposed system consists of two parts. First part is the external quality classification using machine vision system which is based on its shape and mass. The second part is the internal quality classification using near infrared (NIR) spectroscopy, based on its total
soluble solid (TSS) value. An image acquisition platform was built to capture the 3-
Dimensional image of Harumanis mango in a single acquisition. A real-time
measurement calibration technique was developed in this research. Combination of
Fourier descriptor parameters and size-shape parameters was used to recognize the shape
of Harumanis mango. An improved two-dimensional disk method was used to estimate
the volume of Harumanis mango based on the captures image. Then a correlation between
the actual volume and actual mass was derived and used to estimate the mass of
Harumanis mango on inline system. The proposed method can correctly classify the
Harumanis mango according to its shape and mass 94.2% of the time. NIR spectrometer
was used to obtain the reflectance wavelength of the Harumanis mango. The juice from
the mango was obtained and measured with a refractrometer to obtain the actual TSS
value. Then, the acquired NIR wavelength was analysed and correlate with the actual TSS
value using multivariate analysis. A regression value of 0.85 for calibration set was found
from the analysis, which explained that there was a high correlation between the
wavelength and TSS. Stepwise Discriminant analysis method was used to find the
significant wavelength that can be used to determine the maturity stage in real-time
system. Ten wavelength points were selected and verified on the testing set. The
discriminant model can be accurately determined the maturity stage with 85.0% accuracy |
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